Amyloid Aggregation Behavior of Human Calcitonin

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Amyloid Aggregation Behavior of Human Calcitonin Amyloid Aggregation Behavior of Human Calcitonin by Kian Kamgar-Parsi A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Applied Physics) In the University of Michigan 2018 Doctoral Committee: Professor Ayyalusamy Ramamoorthy, Chair Professor Ari Gafni Professor Jennifer P. Ogilvie Professor Duncan G. Steel Professor Sarah Veatch Kian Kamgar-Parsi [email protected] ORCID iD: 0000-0002-6324-8893 © Kian Kamgar-Parsi, 2018 Acknowledgements I first must thank my advisor, Ayyalusamy Ramamoorthy. Rams more than anyone else helped teach me how to become an independent scientist and provided me the freedom to ask and pursue questions wherever my science took me. All the while, he remained available whenever I needed guidance or advice, and the tutelage and support he has provided over the past three years will forever be appreciated. I also must thank my committee members, Professors Ari Gafni, Jennifer Ogilvie, Duncan Steel, and Sarah Veatch. All of them have provided invaluable support and guidance during my time at Michigan. Jennifer’s perceptive questions have led me to expand my lines of inquiry into new and exciting directions. Sarah has motivated me to be aggressive in pursuing my work, and has provided valuable counsel to me throughout the navigation of my graduate studies. I want to give particular thanks to Ari and Duncan for providing me my first opportunity to conduct independent research, and for continuing to be constant sources of support and advice throughout my graduate studies even after I left their lab to join the Ramamoorthy Lab. Their continued mentorship has been invaluable to me during my graduate school career. I have also been fortunate to collaborate with several brilliant scientists during my years in the Ramamoorthy Lab. I thank Dr. Akira Naito for providing me with the peptide necessary for my experiments at Michigan, and for his willingness to share his expertise. I thank Dr. Liu Hong for his collaboration on developing kinetics models for amyloid aggregation. Our early morning/late-night skype sessions always proved productive and stimulating. I would also like to ii thank Dr. Charlie Brooks for his collaboration on molecular dynamics simulations of calcitonin monomers. Charlie’s questions inevitably led me to new and exciting avenues of study, and his willingness to discuss our findings together at length is greatly appreciated. Of course, the majority of my thesis work occurred in the laboratory, and I owe huge thanks to the people of the Ramamoorthy Lab. Dr. Kamal Mroue, Dr. Rongchun Zhang, Dr. Meng Zhang, Dr. Elke Prade, Dr. Thirupati Ravula, Dr. Sam Kotler, Dr. Jeffrey Brender, Dr. Amit Pithadia, Dr. Kyle Korshavn, Dr. Mukesh Mahajan, Dr. Carlo Barnaba, Dr. Bikash Sahoo, Joshua Damron, Katie Gentry, Sarah Cox, Chris MacDonald, Giacomo DiMauro, and Oluseun Oladipo have all been joys to work with and around, and have become friends both inside and outside the lab. Whether discussing confusing experimental results or weekend plans, I always knew I could count on my labmates for help, support, and lunch dates. They will all be sorely missed when I move on in my career. I’d also like to acknowledge Chun-Chieh (Andrew) Chang, for his mentorship in the Gafni-Steel lab when I first started doing graduate research. He taught me a lot about how to be a grad student which served me well over the following four years. I also want to thank my family for the support they have given me throughout my graduate school career. First and foremost, I would like to thank my parents, Behzad and Faezeh. Getting a PhD is difficult, and knowing that they were always available to talk to about research or life or my struggles meant the world to me. The original reasons I grew to love science, they have supported me in my endeavors since I was old enough to endeavor, and I cannot adequately express my gratitude to them for their continued love and support. I want to thank my sister Saman for keeping me grounded and focused, and being goofy when I most needed it. Her pride in me when I am not proud of myself has been a constant boon for me when things get tough. I also want to thank my grandmother Irandokht, my aunts Firouzeh and Avid, my uncle Behrooz, and my cousins iii Nassime, Kurosh, Dariush, Liana, Kaveh, and Pareesa. The occasions where I could visit home were revitalizing, not least of which because I got to see so many people I loved, and that feeling has helped to drive me in my pursuits. iv Table of Contents Acknowledgements………………………………………………………………………………..ii List of Figures……………………………………………………………………...……………..vi List of Appendices……………………………………………………………...………………...ix Abstract…………………………………………………………………………...……………….x Chapter 1: Structural Biology of Calcitonin: from aqueous therapeutic properties to amyloid aggregation…………………..………………………………………………………...…………..1 Chapter 2: Growth-incompetent monomers of human calcitonin lead to a non-canonical direct relationship between peptide concentration and lag time……………………………...…………46 Chapter 3: The role of phospholipid membranes in the amyloid aggregation of human calcitonin …………………………………………………………………………………………………....82 Chapter 4: Conclusions and Perspectives……………………………………………………….103 Appendices…………………………………………………………………………………...…114 v List of Figures Figure 1.1. Amino-acid sequence alignment of the commonly studied human, bovine, porcine, salmon, and eel calcitonin…………………………………………………………………………2 Figure 1.2. Canonical amyloid aggregation pathway………………………………………………4 Figure 1.3. Illustration of the synthesis of calcitonin from the CALC I gene………………………6 Figure 1.4. Transmission electron microscope images of polymorphic solution structures of human calcitonin aggregates formed under different conditions…………………………………………11 Figure 1.5. Solution and solid-state NMR spectra of hCT in various forms………………………13 Figure 1.6. NMR-derived structures of monomer, oligomer, and fibril stages of hCT……………14 Figure 2.1. hCT aggregation exhibits a direct relationship between initial monomer concentration and lag time………………………………………………………………………………………49 Figure 2.2. hCT aggregates slower at higher concentrations under a range of conditions……...…50 Figure 2.3. Concentration-dependent differences in early aggregates of hCT……………………53 Figure 2.4. Pyrene detects a micelle-like oligomer in hCT…………………………….…………56 Figure 2.5. Monomer conversion allows accurate kinetic modeling of observed trend between peptide concentration and lag time………………………………………………….……………58 Figure 2.6. Molecular dynamics simulations implicate α-helical structure as key in determining monomer growth-competence……………………………………………………………………60 Figure 2.7. Circular Dichroism measurements support MD simulations on a-helical propensity...62 Figure 2.8. ThT kinetics assays at pH 5.4 indicate the direct relationship to remain, implicate Asp15 in determining growth-competence…………………………………………….…………65 Figure 3.1. hCT exhibits a direct relationship between peptide concentration and lag phase in a membrane environment……………………………………………………..……………………85 Figure 3.2. DOPC and POPC LUVs slow hCT aggregation in a dose dependent manner…...……86 vi Figure 3.3. Differential absorption flattening in time-course CD experiments indicate different rates of peptide adsorption…………………………………………………….………………….88 Figure 3.4. Remodeling of hCT fibers depends on peptide to lipid ratio…………………...……..91 Figure 3.5. LUVs are capable of remodeling solution-grown hCT fibrils………………...………92 Figure A.1. ThT fluorescence curves of hCT aggregation for TEM……….……………………114 Figure A.2. Seeded ThT assays reveal lag time to not be entirely primary nucleus dependent ………….………………………………………………………………………….……………115 Figure A.3. DLS measurements show no time- or concentration-dependent differences in mass distribution over time between peaks…………………………………...………………………116 Figure A.4. Predictions on fraction of monomers, normalized number concentration of protofibrils, and normalized mass concentration of protofibrils under different initial hCT peptide concentration based on the kinetic model………………………………………………………………………117 Figure A.5. The influence of reaction rate constants on the lag time of hCT fibrillation…….…..118 Figure A.6. Local sensitivity analysis on reaction rates…………………………………………119 Figure A.7. sCT displays lower structural heterogeneity and inreased helical content when compared to hCT, with mutations to the aromatic residues in hCT and hCT at low pH inducing a more sCT-like behavior…………………………………………………………………………120 Figure A.8. TEM image of 120 µM hCT aggregates in late lag phase………...…………………121 Figure B.1. LUVs with higher transition temperatures induce correspondingly larger concentration dependent increases in lag time.………………………………...………………………………122 Figure B.2. CD absorbance over time confirms absorption flattening and signal loss ………………………………………………………………………………………………..…123 Figure B.3. LUVs that slow aggregation increase adsorption and induce enhanced helical structure in hCT at intermediate time points………………………………………………………………124 Figure B.4. DMPC LUVs show more rapid absorption flattening and induce greater helical structure in hCT than DOPC LUVs……………………………………………………………..125 Figure B.5. CD spectra taken after 24 hours of aggregation for hCT grown in a membrane environment show primarily -sheet structures………………...……………………………….126 Figure B.6. ThT signal loss for 10 M hCT fibers is significantly greater than that seen in solution………………………………………………………………………………………….127 vii Figure B.7. Higher temperatures induce fibril remodeling in all LUV compositions
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